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Articles
Published: 2018-12-29

Small Area Estimation dengan Metode Hierarchical Bayes pada Proporsi Destinasi Objek Wisata Halal Kabupaten Lombok Barat

Universitas Mataram
Universitas Mataram
Universitas Mataram
Gibbs Algorithm Metropolis-Hasting Halal Tourism Hierarchical Bayes MCMC Small Area Estimation

Abstract

Research using Hierarchical Bayes (HB) applied to Small Area Estimation (SAE) was conducted with the aim to estimate the proportion of halal tourism destination in West Lombok Regency. The development of halal taourism object in West Lombok that has been done by the Departement of Culture and Tourism, has not been fully able to do direct estimation on a small area, such as at the sub-district level. One way of obtaining estimation data up to the sub-district level is by increasing the sample size. However, increasing the sample size will cost time and money. Therefore, SAE method can be used to solve the poblem of data optimization. Furthermore, the HB method is used in the process of finding the expected alleged value. The prediction process was performed using Markov Chain Monte Carlo (MCMC) by applying the conditional Gibbs Algorithm of Metropolis-Hasting. Indirect modeling using HB method on SAE is based on the Fay-Herriot model for the area level with the help of supporting variables. The estimation results were then compared with the direct estimates with the value of the variance statistic as a benchmark. The results showed that the estimation using HB gave in a smaller average of variance value score of 0.021, compared with direct estimates with an average of variance value of 0.042. This showed that indirect estimation using HB method gave better result than using direct estimation method.

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